Package ai.libs.jaicore.ml.core.filter.sampling.inmemory.stratified.sampling

Interface Summary

Interface	Description
IStratiAmountSelector	Functional interface to write custom logic for selecting the amount of strati for a dataset.
IStratiAssigner	Interface to write custom Assigner for datapoints to strati.

Class Summary

Class	Description
AttributeBasedStratiAmountSelectorAndAssigner	This class is responsible for computing the amount of strati in attribute-based stratified sampling and assigning elements to the strati.
AttributeDiscretizationPolicy
ClusterStratiAssigner
DiscretizationHelper	This helper class provides methods that are required in order to discretize numeric attributes.
GMeansStratiAmountSelectorAndAssigner	Combined strati amount selector and strati assigner via g-means.
KMeansStratiAssigner	Cluster the data set with k-means into k Clusters, where each cluster stands for one stratum.
LabelBasedStratifiedSampling<D extends org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>>
StratifiedSampling<D extends org.api4.java.ai.ml.core.dataset.IDataset<?>>	Implementation of Stratified Sampling: Divide dataset into strati and sample from each of these.

Enum Summary

Enum	Description
DiscretizationHelper.DiscretizationStrategy